{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "%load_ext autoreload\n",
    "%autoreload 2\n",
    "import sys\n",
    "sys.path.append('..')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "from agots.generators.behavior_generators import sine_generator\n",
    "from agots.multivariate_generators.multivariate_data_generator import MultivariateDataGenerator"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>x0</th>\n",
       "      <th>x1</th>\n",
       "      <th>x2</th>\n",
       "      <th>x3</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>x0</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.986455</td>\n",
       "      <td>-0.015893</td>\n",
       "      <td>-0.048035</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>x1</th>\n",
       "      <td>0.986455</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>-0.012629</td>\n",
       "      <td>-0.051007</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>x2</th>\n",
       "      <td>-0.015893</td>\n",
       "      <td>-0.012629</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.340076</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>x3</th>\n",
       "      <td>-0.048035</td>\n",
       "      <td>-0.051007</td>\n",
       "      <td>0.340076</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          x0        x1        x2        x3\n",
       "x0  1.000000  0.986455 -0.015893 -0.048035\n",
       "x1  0.986455  1.000000 -0.012629 -0.051007\n",
       "x2 -0.015893 -0.012629  1.000000  0.340076\n",
       "x3 -0.048035 -0.051007  0.340076  1.000000"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.random.seed(1337)\n",
    "\n",
    "STREAM_LENGTH = 200\n",
    "N = 4\n",
    "K = 2\n",
    "behavior_config = {'amplitude': 0.3}\n",
    "\n",
    "dg = MultivariateDataGenerator(STREAM_LENGTH, N, K, behavior=sine_generator, behavior_config=behavior_config)\n",
    "a = dg.generate_baseline(initial_value_min=-4, initial_value_max=4)\n",
    "\n",
    "for col in a.columns:\n",
    "    plt.plot(a[col], label=col)\n",
    "plt.legend()\n",
    "plt.show()\n",
    "\n",
    "a.corr()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.5"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
